1. Field of the Invention
This invention generally relates to digital communications and, more particularly, to a system and method for minimizing the effects of inter-symbol interference in a data channel of binary coded information, in real-time, using a constantly updated history of corrected bit decisions.
2. Description of the Related Art
FIG. 1 is a diagram illustrating a signal recovered from a binary symmetric, non-dispersive channel in the presence of noise (prior art). Conventionally, the signal is filtered with a transfer function matched to the signaling waveform and thresholded at the voltage level most likely to yield the transmitted bit. To recover the transmitted information, a hard decision must be made on the value of the received bit.
As a function of the filtering process, and sometimes as a result of the transmission process, pulse spreading occurs. That is, the energy associated with a bit spreads to neighboring bits. For small degrees of spreading these effects can be limited to the nearest neighbors with modest degradation in performance.
Three basic types of pulse spreading exist. The first possibility is that both the neighboring bits are a zero (no neighboring bits are a one). The second possibility is that only one of the neighboring bits (either the preceding or subsequent bit) is a one. Alternately stated, only one of the neighboring bits is a zero. The third possibility is that both neighboring bits are one. For each of these cases the likelihood of error in determining a bit value can be minimized if different thresholds are used for different bit combinations.
FIG. 2 is a diagram illustrating received analog waveforms that are part of a serial data stream of digitally encoded data, where the waveforms are distorted in response to the inter-symbol interference resulting from energy dispersion (prior art). The value at the output of the filter varies with each bit, and is essentially a random process, due to the non-deterministic nature of the information, and scrambling that is often used in the transmission of data streams. However, received bits can be characterized with probability density functions (PDFs), as shown. Without knowledge of the neighboring bits, a single probability density function could be extracted that represents the random behavior of the input over all conditions and all sequences. However, conditional probability density functions can be defined for the three cases mentioned above. Namely, probability density functions can be defined for the cases where there are zero neighboring ones, only one neighboring one, and two neighboring ones.
If the bit value decision process could be made using the knowledge of the decision made on the preceding decoded bit, and with a measurement of a subsequent decoded bit, then the corresponding probability density function could be selected to make a more accurate decision on the current bit decision. However, the cost and accuracy of conventional analog-to-digital (A/D) conversion circuits make such a solution impractical.
The degree of dispersion exhibited by a channel, and hence the separation of the conditional probability density functions, varies in response to a number of fixed and variable factors. Effective dispersion mitigation techniques must therefore be easily optimized to the channel and somewhat adaptive to changes in the channel due to aging, temperature changes, reconfiguration, and other possible influences.
There are numerous algorithms and techniques to find the optimum sampling time in a digital communication system. Peak detection with match-filter and early-late gate sampling are two techniques used widely for capturing sampling times. A general early-late gating scheme requires zero-crossing in the waveform. Peak detection match-filter approach is optimum when the channel and the transmitter characteristics are well known. However, early-late gating is difficult to apply if the zero-crossing is unknown. Further, peak detection is not effective without prior knowledge of the transmitter and/or channel characteristics.
It would be advantageous if inter-symbol interference caused by energy dispersion in a received data channel could be minimized.
It would be advantageous if a non-causal channel analysis could be used to minimize the effects of inter-symbol interference, in real-time, based on an analysis history of corrected bit decisions.